Fitness Monitoring System Based on Multimodal Perception and Rotation Strategy

In recent years, Japan has a steady increase in fitness enthusiasts. However, it is accompanied by a rise in injury rate due to improper fitness knowledge. To address this issue, IoT-based fitness assessment systems are gaining attention. However, many existing systems can not simultaneously assess fitness movements and vital signals, and they have challenges in monitoring people in large spaces. Therefore, in this study, we propose a remote fitness monitoring system that employs a collaborative approach with various sensors, including fisheye camera, RGB camera, infrared sensor, and millimeter wave radar. This system enables non-contact monitoring of users' physiological information during fitness, while also evaluating the quality of their movements. Through location detection via image analysis and actuation by servo motor, this system achieves wide- range and continuous monitoring of trainees using a small number of devices. Furthermore, we conduct experiments to validate the system's effectiveness in terms of scalability of the monitoring range and the effectiveness of vital signs monitoring.